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Optimization of Light Intensity and NaNO(3) Concentration in Amazon Cyanobacteria Cultivation to Produce Biodiesel

The objective of this study, for the first time, was to optimize Amazonian cyanobacterial culture conditions for improving cell productivity and lipid content, by analyzing the effect of light intensity and nitrogen concentration, for empirically evaluating biodiesel quality parameters. The strains...

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Detalles Bibliográficos
Autores principales: Aboim, Joseline Barbosa, de Oliveira, Deborah Terra, de Mescouto, Vanessa Albuquerque, dos Reis, André Silva, da Rocha Filho, Geraldo Narciso, Santos, Agenor Valadares, Xavier, Luciana Pereira, Santos, Alberdan Silva, Gonçalves, Evonnildo Costa, do Nascimento, Luis Adriano Santos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6630786/
https://www.ncbi.nlm.nih.gov/pubmed/31238580
http://dx.doi.org/10.3390/molecules24122326
Descripción
Sumario:The objective of this study, for the first time, was to optimize Amazonian cyanobacterial culture conditions for improving cell productivity and lipid content, by analyzing the effect of light intensity and nitrogen concentration, for empirically evaluating biodiesel quality parameters. The strains Synechocystis sp. CACIAM05, Microcystis aeruginosa CACIAM08, Pantanalinema rosaneae CACIAM18, and Limnothrix sp. CACIAM25, were previously identified by morphological and molecular analysis (16S rRNA) and were selected based on their production of chlorophyll a and dry cell weight. Then, factorial planning (2(2)) with central points was applied, with light intensity and NaNO(3) concentration as independent variables. As response variables, cell productivity and lipid content were determined. Statistical analysis indicated that for all strains, the independent variables were statistically significant for cell productivity. Analysis of the fatty acid composition demonstrated diversity in the composition of the fatty acid profile from the experimental planning assays of each strain. The Biodiesel Analyzer software predicted the biodiesel quality parameters. CACIAM05 and CACIAM25 obtained better parameters with low levels of light intensity and NaNO(3) concentration, whereas CACIAM08 and CACIAM18 obtained better parameters with low NaNO(3) concentrations and high luminous intensity.